KAJIAN BENTUK DAN SENSITIVITAS RUMUS INDEKS PI, STORET, CCME UNTUK PENENTUAN STATUS MUTU PERAIRAN SUNGAI TROPIS DI INDONESIA (Assessment of the Forms and Sensitivity of the Index Formula PI, Storet, CCME for The Determination of Water Quality Status)
Bibliographic record
Abstract
ABSTRAK Metode-metode Pollution Index (USA), metode Storet (USA) dan metode CCME (Canada) adalah metode indeks kualitas air (IKA) untuk penentuan status mutu air. Dua yang pertama banyak digunakan praktisi lingkungan di Indonesia karena dirujuk dalam Keputusan Menteri Lingkungan Hidup No. 115/2013. Ketiganya dapat menghitung IKA dengan baku mutu kualitas air lokal sungai kajian. Mengingat negara penyusun metode tersebut berbeda kondisi lingkungannya dan masing-masing metode mempunyai faktor spesifik untuk menghitung IKA, maka perlu dikaji kesesuaian masing-masing metode untuk diterapkan di sungai tropis Indonesia. Masing-masing metode akan dikaji bentuk persamaan dan sensitivitasnya dengan menggunakan banyak parameter kualitas air dan menggunakan jumlah parameter kualitas air tertentu mengacu pada metode IKA yang dikembangkan di negara tropis lainnya. Kajian menggunakan data pemantauan “Prokasih” di sungai Gadjah Wong Yogyakarta tahun 1996/1997 - 2011/2012. Penelitian ini dilakukan dalam rangka menyusun metode IKA sungai tropis Indonesia pada umumnya dan di sungai Gadjah Wong khususnya serta program pengelolaan kualitas air untuk pengendalian pencemaran air sungai, dengan target konservasi air sungai yang multifungsi atau overall/general use(memenuhi kriteria kesehatan air baku, memenuhi kriteria estetika serta kriteria ekologi/aman bagi kehidupan di perairan). Hasil kajian menunjukkan bahwa dibandingkan 2 metode lainnya, metode CCME dinilai paling obyektif (secara statistik) menghitung IKA perairan sungai Gadjah Wong. CCME paling sensitif merespon dinamika indeks mutu air di setiap lokasi pemantauan, lebih universal untuk dapat diaplikasikan di luar negara penyusunnya. Namun untuk diaplikasikan di sungai Gadjah Wong, metode CCME perlu diadaptasi terhadap beberapa hal yaitu jumlah dan jenis parameter kualitas air yang dianggap signifikan, jumlah dan kelas mutu air. Adaptasi mempertimbangkan program pengendalian pencemaran air dan strategi operasional/manajemen aliran sungai yang ekologis dan berkelanjutan. Skor batas dan makna setiap kelas mutu air dalam IKA harus diverifikasi terhadap data lingkungan lain misal hasil biotilik ataupun bioassay sehingga status indeks kualitas air tidak bertentangan dengan kondisi biologi di sungai. Pelibatan parameter bakteriologi kualitas air (Escherichia Coli dan Total Coliform) serta Electric Conductivity/EC sebagai parameter kualitas air signifikan dalam metode IKA masih perlu dikaji lebih lanjut untuk pengembangan metode IKA khas perairan sungai di negara tropis Indonesia. ABSTRACT Pollution Index method (USA), Storet method (USA) and CCME (Canada) method are water quality index (WQI) methods used to determine water quality status of a river, the first two are widely used by environmental practioners in Indonesia since it is referred by Environmental Ministry Regulation No. 115/2003. These methods can be used based on local water quality standard. Considering that the country of WQI methods were developed have different environmental condition and each method has its own characteristics to calculate the index, it is necessary to review a suitable WQI method for Indonesia tropical stream in general and for Gadjah Wong stream in particular. This research reviewed the form of the formula of each index, then analyze the sensitivity of each index by using many water quality parameters with and without bacteriology, and reducing the number of water quality parameters similar to those WQI index developed in other tropical countries. Indexes are reviewed using “Prokasih” (Clean River Program) monitoring data at Gadjah Wong stream from 1996/1997 to 2011/2012. Water quality statuses are reviewed in the contex of river water quality management for water pollution prevention, with the target of river water conservation which is “multifunction” or “overall/generall use” to meet health criteria for raw water, aesthetical criteria and ecological safety for aquatic life. Research conclusion showed that compared to the other 2 methods, CCME is considered as the most objective (statistically) to determine water quality index for river waters. It is also the most sensitive to respond to the dynamic of water quality index at each monitoring location (spatial & temporal). This method is also considered as more universally applicable outside of the country it was developed. To be applied at Gadjah Wong stream however, CCME index method needs to be adapted on the number and types of significant water quality parameters. The number of quality status classes of CCME index should be limited to simplify water quality management as well as ecological and sustainability of operational & management strategy. Score limit of every class and significance of water quality classes need to be verified againts other environmental data such as results from biomonitoring and bioassay, the status results of the water quality index should not contradict with the stream biological condition. The use of bacteriology (Escherichia Coli and Total Coliform) and Electrical Conductivity/EC water quality parameters as criteria should be further reviewed for development of WQI method specific for Indonesia tropical stream
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".